Data Quality with SPSS PDF Download

Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Data Quality with SPSS PDF full book. Access full book title Data Quality with SPSS by Christian Fg Schendera. Download full books in PDF and EPUB format.

Data Quality with SPSS

Data Quality with SPSS PDF Author: Christian Fg Schendera
Publisher:
ISBN:
Category :
Languages : en
Pages : 452

Book Description
This world-wide only book about data quality with SPSS provides you with a real Swiss Army knife:● Learn about data quality● Recognize data problems● Understand consequences of data problems● Solve data problems = establish data quality● Communicate data quality This book systematically presents the most important criteria for data quality with SPSS: Completeness, consistency, plausibility and how to deal with duplicates, missings and outliers. And in later chapters some more.The book contains countless real-world examples, from typical dirty data desasters you find in the daily news to the interesting role of outliers in questioning original expectations regarding the ozone concentration over Antarctica. Chapter 1: The most common problem areas, e.g. completeness, uniformity, duplicates, missings, outliers and plausibility. A scheme illustrates the interrelationships of the criteria and the fundamental importance of the quality of data. Further criteria for the quality of data, as well as their communication, are presented in chapters 13 and 19. Chapter 2: Basic conditions for the production of data quality, among other things resources, the prioritization of goals (relevance) and control by protocols (SPSS syntax). Chapter 3: First control possibilities for the completeness of data sets, cases (rows), variables (columns) and values or missings. Chapter 4: Numerous possibilities to identify inconsistencies or to standardize in numerical values, time units and strings.Chapter 5: Identify, understand and (if necessary) filter multiple values or data rows. Chapter 6: Dealing with missing data. After assessing causes (patterns), consequences, extent and mechanisms, numerous methods of handling are discussed, from imputation to multivariate estimates (MVA). Chapter 7: Identify, understand and handle outliers. The special role of expectation ("frames") is discussed. Chapter 8: Qualitative and quantitative approaches to plausibility testing. The examination of the multivariate quality of data is presented using a qualitative and also a quantitative (anomaly) approach. Chapter 9: Checking several variables and criteria by means of validation rules ("Validation" or SPSS procedure VALIDATEDATA). Chapter 10: Numerous examples for checking several values, rows and columns in a data set at once. The numerous variants of counting variables (counters) presented are likely to be of particular interest. Chapter 11: Numerous other examples of working with several (separate) data sets at once, e.g. using macros to screen, split or merge several data sets. Chapter 12: Time or date-related problems, and how to recognize and solve them. Chapter 13: Further criteria for the quality of data, e.g. quantity, unambiguity, relevance, accuracy or comprehensibility. Chapters 14 to 18 contain a small exercise (Chapter 14), a program example for the implementation of a first strategy (Chapter 15), and notes for Macintosh Users (Chapter 17).Chapter 16: Nodes for data quality and data preparation in IBM SPSS Modeler. Chapter 18 contains a list of selected criteria that users can use to log the way in which quality criteria are implemented.Chapter 19 provides annotated criteria for communicating the quality of data, surveys and analyses, including the correct interpretation and communication of the concept of significance. A separate chapter highlights the "deadly sins" of professional work. And their not so pretty consequences. This book is important for all those who work with SPSS and whose results depend on reliable data. Data quality is not everything, but without data quality everything is nothing.

Data Quality with SPSS

Data Quality with SPSS PDF Author: Christian Fg Schendera
Publisher:
ISBN:
Category :
Languages : en
Pages : 452

Book Description
This world-wide only book about data quality with SPSS provides you with a real Swiss Army knife:● Learn about data quality● Recognize data problems● Understand consequences of data problems● Solve data problems = establish data quality● Communicate data quality This book systematically presents the most important criteria for data quality with SPSS: Completeness, consistency, plausibility and how to deal with duplicates, missings and outliers. And in later chapters some more.The book contains countless real-world examples, from typical dirty data desasters you find in the daily news to the interesting role of outliers in questioning original expectations regarding the ozone concentration over Antarctica. Chapter 1: The most common problem areas, e.g. completeness, uniformity, duplicates, missings, outliers and plausibility. A scheme illustrates the interrelationships of the criteria and the fundamental importance of the quality of data. Further criteria for the quality of data, as well as their communication, are presented in chapters 13 and 19. Chapter 2: Basic conditions for the production of data quality, among other things resources, the prioritization of goals (relevance) and control by protocols (SPSS syntax). Chapter 3: First control possibilities for the completeness of data sets, cases (rows), variables (columns) and values or missings. Chapter 4: Numerous possibilities to identify inconsistencies or to standardize in numerical values, time units and strings.Chapter 5: Identify, understand and (if necessary) filter multiple values or data rows. Chapter 6: Dealing with missing data. After assessing causes (patterns), consequences, extent and mechanisms, numerous methods of handling are discussed, from imputation to multivariate estimates (MVA). Chapter 7: Identify, understand and handle outliers. The special role of expectation ("frames") is discussed. Chapter 8: Qualitative and quantitative approaches to plausibility testing. The examination of the multivariate quality of data is presented using a qualitative and also a quantitative (anomaly) approach. Chapter 9: Checking several variables and criteria by means of validation rules ("Validation" or SPSS procedure VALIDATEDATA). Chapter 10: Numerous examples for checking several values, rows and columns in a data set at once. The numerous variants of counting variables (counters) presented are likely to be of particular interest. Chapter 11: Numerous other examples of working with several (separate) data sets at once, e.g. using macros to screen, split or merge several data sets. Chapter 12: Time or date-related problems, and how to recognize and solve them. Chapter 13: Further criteria for the quality of data, e.g. quantity, unambiguity, relevance, accuracy or comprehensibility. Chapters 14 to 18 contain a small exercise (Chapter 14), a program example for the implementation of a first strategy (Chapter 15), and notes for Macintosh Users (Chapter 17).Chapter 16: Nodes for data quality and data preparation in IBM SPSS Modeler. Chapter 18 contains a list of selected criteria that users can use to log the way in which quality criteria are implemented.Chapter 19 provides annotated criteria for communicating the quality of data, surveys and analyses, including the correct interpretation and communication of the concept of significance. A separate chapter highlights the "deadly sins" of professional work. And their not so pretty consequences. This book is important for all those who work with SPSS and whose results depend on reliable data. Data quality is not everything, but without data quality everything is nothing.

SPSS Statistics for Data Analysis and Visualization

SPSS Statistics for Data Analysis and Visualization PDF Author: Keith McCormick
Publisher: John Wiley & Sons
ISBN: 1119003555
Category : Computers
Languages : en
Pages : 528

Book Description
Dive deeper into SPSS Statistics for more efficient, accurate, and sophisticated data analysis and visualization SPSS Statistics for Data Analysis and Visualization goes beyond the basics of SPSS Statistics to show you advanced techniques that exploit the full capabilities of SPSS. The authors explain when and why to use each technique, and then walk you through the execution with a pragmatic, nuts and bolts example. Coverage includes extensive, in-depth discussion of advanced statistical techniques, data visualization, predictive analytics, and SPSS programming, including automation and integration with other languages like R and Python. You'll learn the best methods to power through an analysis, with more efficient, elegant, and accurate code. IBM SPSS Statistics is complex: true mastery requires a deep understanding of statistical theory, the user interface, and programming. Most users don't encounter all of the methods SPSS offers, leaving many little-known modules undiscovered. This book walks you through tools you may have never noticed, and shows you how they can be used to streamline your workflow and enable you to produce more accurate results. Conduct a more efficient and accurate analysis Display complex relationships and create better visualizations Model complex interactions and master predictive analytics Integrate R and Python with SPSS Statistics for more efficient, more powerful code These "hidden tools" can help you produce charts that simply wouldn't be possible any other way, and the support for other programming languages gives you better options for solving complex problems. If you're ready to take advantage of everything this powerful software package has to offer, SPSS Statistics for Data Analysis and Visualization is the expert-led training you need.

Clinical Analytics and Data Management for the DNP, Second Edition

Clinical Analytics and Data Management for the DNP, Second Edition PDF Author: Martha L. Sylvia, PhD, MBA, RN
Publisher: Springer Publishing Company
ISBN: 0826142788
Category : Medical
Languages : en
Pages : 396

Book Description
Praise for the First Edition: “DNP students may struggle with data management, since their projects are not research, but quality improvement, and this book covers the subject well. I recommend it for DNP students for use during their capstone projects." Score: 98, 5 Stars --Doody's Medical Reviews This is the only text to deliver the strong data management knowledge and skills that are required competencies for all DNP students. It enables readers to design data tracking and clinical analytics in order to rigorously evaluate clinical innovations/programs for improving clinical outcomes, and to document and analyze change. The second edition is greatly expanded and updated to address major changes in our health care environment. Incorporating faculty and student input, it now includes modalities such as SPSS, Excel, and Tableau to address diverse data management tasks. Eleven new chapters cover the use of big data analytics, ongoing progress towards value-based payment, the ACA and its future, shifting of risk and accountability to hospitals and clinicians, advancement of nursing quality indicators, and new requirements for Magnet certification. The text takes the DNP student step by step through the complete process of data management from planning to presentation, and encompasses the scope of skills required for students to apply relevant analytics to systematically and confidently tackle the clinical interventions data obtained as part of the DNP student project. Of particular value is a progressive case study illustrating multiple techniques and methods throughout the chapters. Sample data sets and exercises, along with objectives, references, and examples in each chapter, reinforce information. Key Features: Provides extensive content for rigorously evaluating DNP innovations/projects Takes DNP students through the complete process of data management from planning through presentation Includes a progressive case study illustrating multiple techniques and methods Offers very specific examples of application and utility of techniques Delivers sample data sets, exercises, PowerPoint slides and more, compiled in Supplemental Materials and an Instructor Manual

Advanced SQL with SAS

Advanced SQL with SAS PDF Author: Christian FG Schendera
Publisher: SAS Institute
ISBN: 1955977895
Category : Computers
Languages : en
Pages : 428

Book Description
This book introduces advanced techniques for using PROC SQL in SAS. If you are a SAS programmer, analyst, or student who has mastered the basics of working with SQL, Advanced SQL with SAS® will help take your skills to the next level. Filled with practical examples with detailed explanations, this book demonstrates how to improve performance and speed for large data sets. Although the book addresses advanced topics, it is designed to progress from the simple and manageable to the complex and sophisticated. In addition to numerous tuning techniques, this book also touches on implicit and explicit pass-throughs, presents alternative SAS grid- and cloud-based processing environments, and compares SAS programming languages and approaches including FedSQL, CAS, DS2, and hash programming. Other topics include: Missing values and data quality with audit trails “Blind spots” like how missing values can affect even the simplest calculations and table joins SAS macro language and SAS macro programs SAS functions Integrity constraints SAS Dictionaries SAS Compute Server

Sample Surveys: Design, Methods and Applications

Sample Surveys: Design, Methods and Applications PDF Author:
Publisher: Elsevier
ISBN: 9780080932217
Category : Mathematics
Languages : en
Pages : 722

Book Description
This new handbook contains the most comprehensive account of sample surveys theory and practice to date. It is a second volume on sample surveys, with the goal of updating and extending the sampling volume published as volume 6 of the Handbook of Statistics in 1988. The present handbook is divided into two volumes (29A and 29B), with a total of 41 chapters, covering current developments in almost every aspect of sample surveys, with references to important contributions and available software. It can serve as a self contained guide to researchers and practitioners, with appropriate balance between theory and real life applications. Each of the two volumes is divided into three parts, with each part preceded by an introduction, summarizing the main developments in the areas covered in that part. Volume 29A deals with methods of sample selection and data processing, with the later including editing and imputation, handling of outliers and measurement errors, and methods of disclosure control. The volume contains also a large variety of applications in specialized areas such as household and business surveys, marketing research, opinion polls and censuses. Volume 29B is concerned with inference, distinguishing between design-based and model-based methods and focusing on specific problems such as small area estimation, analysis of longitudinal data, categorical data analysis and inference on distribution functions. The volume contains also chapters dealing with case-control studies, asymptotic properties of estimators and decision theoretic aspects. Comprehensive account of recent developments in sample survey theory and practice Discusses a wide variety of diverse applications Comprehensive bibliography

Data Analysis with IBM SPSS Statistics

Data Analysis with IBM SPSS Statistics PDF Author: Kenneth Stehlik-Barry
Publisher: Packt Publishing Ltd
ISBN: 1787280705
Category : Computers
Languages : en
Pages : 446

Book Description
Master data management & analysis techniques with IBM SPSS Statistics 24 About This Book Leverage the power of IBM SPSS Statistics to perform efficient statistical analysis of your data Choose the right statistical technique to analyze different types of data and build efficient models from your data with ease Overcome any hurdle that you might come across while learning the different SPSS Statistics concepts with clear instructions, tips and tricks Who This Book Is For This book is designed for analysts and researchers who need to work with data to discover meaningful patterns but do not have the time (or inclination) to become programmers. We assume a foundational understanding of statistics such as one would learn in a basic course or two on statistical techniques and methods. What You Will Learn Install and set up SPSS to create a working environment for analytics Techniques for exploring data visually and statistically, assessing data quality and addressing issues related to missing data How to import different kinds of data and work with it Organize data for analytical purposes (create new data elements, sampling, weighting, subsetting, and restructure your data) Discover basic relationships among data elements (bivariate data patterns, differences in means, correlations) Explore multivariate relationships Leverage the offerings to draw accurate insights from your research, and benefit your decision-making In Detail SPSS Statistics is a software package used for logical batched and non-batched statistical analysis. Analytical tools such as SPSS can readily provide even a novice user with an overwhelming amount of information and a broad range of options for analyzing patterns in the data. The journey starts with installing and configuring SPSS Statistics for first use and exploring the data to understand its potential (as well as its limitations). Use the right statistical analysis technique such as regression, classification and more, and analyze your data in the best possible manner. Work with graphs and charts to visualize your findings. With this information in hand, the discovery of patterns within the data can be undertaken. Finally, the high level objective of developing predictive models that can be applied to other situations will be addressed. By the end of this book, you will have a firm understanding of the various statistical analysis techniques offered by SPSS Statistics, and be able to master its use for data analysis with ease. Style and approach Provides a practical orientation to understanding a set of data and examining the key relationships among the data elements. Shows useful visualizations to enhance understanding and interpretation. Outlines a roadmap that focuses the process so decision regarding how to proceed can be made easily.

Real-time Fraud Detection Analytics on IBM System z

Real-time Fraud Detection Analytics on IBM System z PDF Author: Mike Ebbers
Publisher: IBM Redbooks
ISBN: 0738437638
Category : Computers
Languages : en
Pages : 70

Book Description
Payment fraud can be defined as an intentional deception or misrepresentation that is designed to result in an unauthorized benefit. Fraud schemes are becoming more complex and difficult to identify. It is estimated that industries lose nearly $1 trillion USD annually because of fraud. The ideal solution is where you avoid making fraudulent payments without slowing down legitimate payments. This solution requires that you adopt a comprehensive fraud business architecture that applies predictive analytics. This IBM® Redbooks® publication begins with the business process flows of several industries, such as banking, property/casualty insurance, and tax revenue, where payment fraud is a significant problem. This book then shows how to incorporate technological advancements that help you move from a post-payment to pre-payment fraud detection architecture. Subsequent chapters describe a solution that is specific to the banking industry that can be easily extrapolated to other industries. This book describes the benefits of doing fraud detection on IBM System z®. This book is intended for financial decisionmakers, consultants, and architects, in addition to IT administrators.

Rasch Analysis in the Human Sciences

Rasch Analysis in the Human Sciences PDF Author: William J. Boone
Publisher: Springer Science & Business Media
ISBN: 9400768575
Category : Science
Languages : en
Pages : 482

Book Description
Rasch Analysis in the Human Sciences helps individuals, both students and researchers, master the key concepts and resources needed to use Rasch techniques for analyzing data from assessments to measure variables such as abilities, attitudes, and personality traits. Upon completion of the text, readers will be able to confidently evaluate the strengths and weakness of existing instrumentation, compute linear person measures and item measures, interpret Wright Maps, utilize Rasch software, and understand what it means to measure in the Human Sciences. Each of the 24 chapters presents a key concept using a mix of theory and application of user-friendly Rasch software. Chapters also include a beginning and ending dialogue between two typical researchers learning Rasch, "Formative Assessment Check Points," sample data files, an extensive set of application activities with answers, a one paragraph sample research article text integrating the chapter topic, quick-tips, and suggested readings. Rasch Analysis in the Human Sciences will be an essential resource for anyone wishing to begin, or expand, their learning of Rasch measurement techniques, be it in the Health Sciences, Market Research, Education, or Psychology.

Ethical Challenges in the Management of Health Information

Ethical Challenges in the Management of Health Information PDF Author: Laurinda B. Harman
Publisher: Jones & Bartlett Learning
ISBN: 9780834212299
Category : Medical
Languages : en
Pages : 387

Book Description
Resource added for the Health Information Technology program 105301.

Knowledge Management

Knowledge Management PDF Author: Tapan K Panda
Publisher: Excel Books India
ISBN: 9788174466211
Category : Industrial management
Languages : en
Pages : 222

Book Description
The idea of managing and transforming tacit to explicit knowledge is getting more and more attention in public systems domain. It has been quite sometime that authors, researchers and managers have come to realize that employees, processes and systems of decision-making in the organizations are a great reservoir of tacit knowledge. It is an important challenge to build and manage systems that can capture, store, retrieve and build new knowledge base for effective decision-making and yet have a human interface. This book is an eye opener for people having interest in knowledge management and knowledge management systems in modern organizations. This book covers ideas, models, conceptual papers and case studies covering the whole globe through the lenses of authors of different continents. For good governance and effective management of public systems, the authors have developed knowledge management processes, models and systems that can have universal appeal and applicability. The book has sixteen, well researched, thought provoking papers and case studies from India, Europe, Brazil and USA. The judicious mix of conceptual papers and case studies will help the students/managers to understand and internalize the process and stages of knowledge management from different countries. It will also make them visualize the practice of knowledge management across the diverse organizations and countries.